Since machine learning is an important domain of 6G, we must explore different machine learning algorithms to examine the impacts of them on different performance factors of 6G. Generalising the machine learning process will not provide satisfactory results for frequently added data in an application. We must keep preferable federated learning on the top priority list in machine learning applications, however they also suffer from fairness issues [1]}, [2]}. The transfer learning can be an efficient-approach for making the 6G system adaptable with the wireless environment [3]}.
